U.S. patent application number 16/000078 was filed with the patent office on 2019-12-05 for managing material delivery productivity.
This patent application is currently assigned to Caterpillar Inc.. The applicant listed for this patent is Caterpillar Inc.. Invention is credited to Chris Ha, Chau Le, Tony Metzger.
Application Number | 20190370726 16/000078 |
Document ID | / |
Family ID | 67138022 |
Filed Date | 2019-12-05 |
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United States Patent
Application |
20190370726 |
Kind Code |
A1 |
Ha; Chris ; et al. |
December 5, 2019 |
MANAGING MATERIAL DELIVERY PRODUCTIVITY
Abstract
A device for managing material delivery productivity is
disclosed. The device may receive information identifying a job
site, a load zone, a dump zone, a quantity of loads, and a
material. The device may provide, to a user device associated with
a machine, information indicating that the load zone, the dump
zone, the quantity of loads, and the material are assigned to the
machine, and may receive, over a time period, location information
associated with the machine. The device may determine statuses of
the machine over the time period and based on the location
information, and may calculate a dump count of the material and a
quantity of material delivery cycles, for the machine and at a
particular time, based on the statuses of the machine. The device
may perform an action based on the dump count of the material and
the quantity of material delivery cycles.
Inventors: |
Ha; Chris; (Champaign,
IL) ; Le; Chau; (Urbana, IL) ; Metzger;
Tony; (Congerville, IL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Caterpillar Inc. |
Deerfield |
IL |
US |
|
|
Assignee: |
Caterpillar Inc.
Deerfield
IL
|
Family ID: |
67138022 |
Appl. No.: |
16/000078 |
Filed: |
June 5, 2018 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06Q 10/063114 20130101;
G06Q 50/02 20130101; G01C 21/3682 20130101; G06Q 50/08 20130101;
G06F 3/04883 20130101; H04W 4/021 20130101 |
International
Class: |
G06Q 10/06 20060101
G06Q010/06; G01C 21/36 20060101 G01C021/36; H04W 4/021 20060101
H04W004/021; G06F 3/0488 20060101 G06F003/0488 |
Claims
1. A device comprising: one or more memory devices; and one or more
processors, operatively coupled to the one or more memory devices,
to: receive information identifying a job site, a load zone of the
job site, a dump zone of the job site, a quantity of loads, and a
material associated with the load zone and the dump zone; provide,
to a user device associated with a machine, information indicating
that the load zone, the dump zone, the quantity of loads, and the
material are assigned to the machine; receive, from the user device
and over a time period, location information associated with the
user device and the machine; determine statuses of the machine over
the time period and based on the location information; calculate a
dump count of the material, for the machine and at a particular
time, based on the statuses of the machine; calculate a quantity of
material delivery cycles, for the machine and at the particular
time, based on the statuses of the machine; and perform an action
based on the dump count of the material and the quantity of
material delivery cycles.
2. The device of claim 1, wherein the information identifying the
load zone of the job site and the dump zone of the job site is
provided via geographical boundaries that are input to a user
interface displaying a visual rendering of the job site.
3. The device of claim 1, wherein the user device is a first user
device, and wherein, when performing the action, the one or more
processors are to one or more of: provide, to a second user device,
information identifying the dump count of the material and the
quantity of material delivery cycles, provide, to the first user
device, an update to the information indicating that the load zone,
the dump zone, the quantity of loads, and the material are assigned
to the machine, or provide, to a third user device associated with
another machine, information indicating that the load zone, the
dump zone, a portion of the quantity of loads, and the material are
assigned to the other machine.
4. The device of claim 1, wherein the one or more processors, when
calculating the dump count of the material, are to: determine,
based on the statuses of the machine, a first quantity of times the
machine is located at or near the load zone; determine, based on
the statuses of the machine, a second quantity of times the machine
is located between the load zone and the dump zone; determine,
based on the statuses of the machine, a third quantity of times the
machine is located at or near the dump zone; and calculate the dump
count of the material based on the first quantity of times, the
second quantity of times, and the third quantity of times.
5. The device of claim 1, wherein the one or more processors, when
calculating the quantity of material delivery cycles, are to:
determine, based on the statuses of the machine, a first quantity
of times the machine is located at or near the load zone;
determine, based on the statuses of the machine, a second quantity
of times the machine is traveling from the load zone to the dump
zone; determine, based on the statuses of the machine, a third
quantity of times the machine is located at or near the dump zone;
determine, based on the statuses of the machine, a fourth quantity
of times the machine is traveling from the dump zone to the load
zone; and calculate the quantity of material delivery cycles based
on the first quantity of times, the second quantity of times, the
third quantity of times, and the fourth quantity of times.
6. The device of claim 1, wherein the one or more processors are
further to: identify the machine based on the information
identifying the job site, the load zone, the dump zone, the
quantity of loads, and the material, and wherein the one or more
processors, when providing the information indicating that the load
zone, the dump zone, the quantity of loads, and the material are
assigned to the machine, are to: provide, to the user device, the
information indicating that the load zone, the dump zone, the
quantity of loads, and the material are assigned to the machine,
based on identifying the machine.
7. The device of claim 1, wherein the machine includes a dump
truck.
8. A non-transitory computer-readable medium storing instructions,
the instructions comprising: one or more instructions that, when
executed by one or more processors of a device, cause the one or
more processors to: receive, from a first user device, information
identifying the job site, a load zone of the job site, a dump zone
of the job site, a quantity of loads, and a material associated
with the load zone and the dump zone; identify a machine, from a
plurality of machines, to assign to the load zone, the dump zone,
the quantity of loads, and the material, based on information
associated with the plurality of machines; provide, to a second
user device associated with the machine, and based on the
information identifying the machine, information indicating that
the load zone, the dump zone, the quantity of loads, and the
material are assigned to the machine; receive, from the second user
device and over a time period, location information associated with
the second user device and the machine; determine statuses of the
machine over the time period and based on the location information;
calculate a dump count of the material, for the machine and at a
particular time, based on the statuses of the machine; calculate a
quantity of material delivery cycles, for the machine and at the
particular time, based on the statuses of the machine; and perform
an action based on the dump count of the material and the quantity
of material delivery cycles.
9. The non-transitory computer-readable medium of claim 8, wherein
the action includes one or more of: providing, to the first user
device or the second user device, information identifying the dump
count of the material and the quantity of material delivery cycles,
providing, to the first user device, one or more alerts associated
with the dump count of the material or the quantity of material
delivery cycles, providing, to the second user device, an update to
the information indicating that the load zone, the dump zone, the
quantity of loads, and the material are assigned to the machine, or
providing, to a third user device associated with another machine,
information indicating that the load zone, the dump zone, a portion
of the quantity of loads, and the material are assigned to the
other machine.
10. The non-transitory computer-readable medium of claim 8, wherein
the information identifying the load zone of the job site is
determined based on a location of a loader machine on the job site,
and wherein the information identifying the dump zone of the job
site is provided via geographical boundaries that are input to a
user interface displaying a visual representation of the job
site.
11. The non-transitory computer-readable medium of claim 8, wherein
the one or more instructions, that cause the one or more processors
to calculate the dump count of the material, cause the one or more
processors to: determine, based on the statuses of the machine, a
quantity of times that the machine is located at or near the load
zone, then is located between the load zone and the dump zone, and
then is located at or near the dump zone; and calculate the dump
count of the material based on the quantity of times.
12. The non-transitory computer-readable medium of claim 8, wherein
the one or more instructions, that cause the one or more processors
to calculate the quantity of material delivery cycles, cause the
one or more processors to: determine, based on the statuses of the
machine, a quantity of times that the machine is located at or near
the load zone, then is traveling from the load zone to the dump
zone, then is located at or near the dump zone, and then is
traveling from the dump zone to the load zone; and calculate the
quantity of material delivery cycles based on the quantity of
times.
13. The non-transitory computer-readable medium of claim 8, wherein
the statuses of the machine indicate one or more of: that the
machine is at or near the load zone when the machine is located
within a first distance of the load zone for a first amount of
time, that the machine is traveling from the load zone to the dump
zone when the machine is located greater than the first distance
from the load zone for a second amount of time after the first
amount of time, that the machine is at or near the dump zone when
the machine is located within a second distance of the dump zone
for a third amount of time, or that the machine is traveling from
the dump zone to the load zone when the machine is located greater
than the second distance from the dump zone for a fourth amount of
time after the third amount of time.
14. The non-transitory computer-readable medium of claim 8, further
comprising: one or more instructions that, when executed by the one
or more processors, cause the one or more processors to: monitor
the job site based on the statuses of the machine and based on
statuses of another machine on the job site; generate one or more
alerts based on monitoring the job site; and provide the one or
more alerts to the first user device.
15. A method comprising: receiving, by a device, information
identifying a job site, a load zone of the job site, a dump zone of
the job site, a quantity of loads, and a material associated with
the load zone and the dump zone; identifying, by the device, a
machine from a plurality of machines available for the job site,
based on information about the plurality of machines, information
about drivers of the plurality of machines, information about a
geographical area in which the load zone and the dump zone are
located, or information about a condition associated with the
geographical area; providing, by the device and to a user device
associated with the machine, information indicating that the load
zone, the dump zone, the quantity of loads, and the material are
assigned to the machine; receiving, by the device, from the user
device, and over a time period, location information associated
with the user device and the machine; determining, by the device,
statuses of the machine over the time period and based on the
location information; calculating, by the device, a dump count of
the material, for the machine and at a particular time, based on
the statuses of the machine; and performing, by the device, an
action based on the dump count of the material.
16. The method of claim 15, further comprising: calculating a
quantity of material delivery cycles, for the machine and at the
particular time, based on the statuses of the machine.
17. The method of claim 15, wherein the user device is a first user
device, and wherein performing the action comprises one or more of:
providing, to a second user device, information identifying the
dump count of the material, providing, to the first user device, an
update to the information indicating that the load zone, the dump
zone, the quantity of loads, and the material are assigned to the
machine, or providing, to a third user device associated with
another machine, information indicating that the load zone, the
dump zone, a portion of the quantity of loads, and the material are
assigned to the other machine.
18. The method of claim 15, wherein calculating the dump count of
the material comprises: determining, based on the statuses of the
machine, a quantity of times that the machine is located at or near
the load zone, then is located between the load zone and the dump
zone, and then is located at or near the dump zone; and calculating
the dump count of the material based on the quantity of times.
19. The method of claim 15, wherein the statuses of the machine
indicate one or more of: that the machine is loading the material
at the load zone when the machine is located within a first
distance of the load zone for a first amount of time, that the
machine is hauling the material from the load zone to the dump zone
when the machine is located greater than the first distance from
the load zone for a second amount of time after the first amount of
time, that the machine is dumping the material at the dump zone
when the machine is located within a second distance of the dump
zone for a third amount of time, or that the machine is returning
from the dump zone to the load zone when the machine is located
greater than the second distance from the dump zone for a fourth
amount of time after the third amount of time.
20. The method of claim 15, further comprising: monitoring the job
site based on the statuses of the machine; generating material
delivery productivity information based on monitoring the job site;
and providing the material delivery productivity information to
another user device.
Description
TECHNICAL FIELD
[0001] The present disclosure relates generally to material
delivery, and, more particularly, to a management platform that
manages material delivery productivity.
BACKGROUND
[0002] A construction job site may include multiple earth-moving
machines, such as dump trucks, excavators, continuous miners,
loaders, and/or the like, and responsible persons associated with
different machines. The machines often engage with and/or move a
variety of earthen materials from one location of a job site to
another location of the job site or another job site. Operators of
the machines may be compensated based on quantities of material
loads delivered, moved, processed, and/or the like. The machines
may also be tracked to determine the quantities of material loads
and the productivity of the machines.
[0003] Conventional techniques for tracking machines and
determining machine productivity include utilizing telemetry data
provided by embedded or retrofit hardware attached to the machines
at job sites. Such telemetry data may be used in an effort to
improve earth-moving productivity. However, the embedded or
retrofit hardware is expensive, and many job sites have complex
material processing situations and/or utilize short-term, rented
machines that do not have the embedded or retrofit hardware. As a
result, the telemetry data received from the hardware may be
incorrect or nonexistent, and determining machine productivity may
require manual validation of the quantities of material loads.
[0004] One worksite system is disclosed in U.S. Patent Application
Publication No. 2010/0312599 that published in the name of Durst on
Dec. 9, 2010 ("the '599 patent publication"). In particular, the
'599 patent publication discloses a worksite system for measuring
productivity of a machine. The worksite system may generate a
digital map of a worksite with geo-fences defined. Each different
geo-fence may be marked and may demarcate a subsection of the area
represented by the digital map. A machine may be represented on the
digital map, and may not be inside or at a perimeter of any of the
geo-fences. This information may be reported by the worksite system
to a worksite manager and/or a machine operator and may be useful
in helping to assess a productivity of the machine. The machine may
include an interface control device that includes components for
automatically gathering information from the machine during the
operation of the machine. For example, the interface control device
may include a locating device, an interface control module, and a
controller for communicating with the worksite system.
[0005] While the worksite system of the '599 patent publication
discloses defining geo-fences for a worksite and tracking
information from the machine, the interface control device may be
hardware that is embedded or retrofit into the machine.
Furthermore, the interface control device may be expensive,
complex, and difficult to operate for a machine operator. Thus, the
interface control device may be incorrectly operated or may not be
utilized at all by the machine operator.
[0006] The management platform of the present disclosure solves one
or more of the problems set forth above and/or other problems in
the art.
SUMMARY
[0007] In one aspect, the present disclosure is related to a device
that includes one or more memory devices, and one or more
processors, operatively coupled to the one or more memory devices,
to receive information identifying a job site, a load zone of the
job site, a dump zone of the job site, a quantity of loads, and a
material associated with the load zone and the dump zone. The one
or more processors may provide, to a user device associated with a
machine, information indicating that the load zone, the dump zone,
the quantity of loads, and the material are assigned to the
machine, and may receive, from the user device and over a time
period, location information associated with the user device and
the machine. The one or more processors may determine statuses of
the machine over the time period and based on the location
information, and may calculate a dump count of the material, for
the machine and at a particular time, based on the statuses of the
machine. The one or more processors may calculate a quantity of
material delivery cycles, for the machine and at the particular
time, based on the statuses of the machine, and may perform an
action based on the dump count of the material and the quantity of
material delivery cycles.
[0008] In another aspect, the present disclosure is related to a
non-transitory computer-readable medium storing instructions that
include one or more instructions that, when executed by one or more
processors of a device, cause the one or more processors to
receive, from a first user device, information identifying the job
site, a load zone of the job site, a dump zone of the job site, a
quantity of loads, and a material associated with the load zone and
the dump zone. The one or more instructions may cause the one or
more processors to identify a machine, from multiple machines, to
assign to the load zone, the dump zone, the quantity of loads, and
the material, based on information associated with the multiple
machines. The one or more instructions may cause the one or more
processors to provide, to a second user device associated with the
machine, and based on the information identifying the machine,
information indicating that the load zone, the dump zone, the
quantity of loads, and the material are assigned to the machine,
and receive, from the second user device and over a time period,
location information associated with the second user device and the
machine. The one or more instructions may cause the one or more
processors to determine statuses of the machine over the time
period and based on the location information, and calculate a dump
count of the material, for the machine and at a particular time,
based on the statuses of the machine. The one or more instructions
may cause the one or more processors to calculate a quantity of
material delivery cycles, for the machine and at the particular
time, based on the statuses of the machine, and perform an action
based on the dump count of the material and the quantity of
material delivery cycles.
[0009] In yet another aspect, the present disclosure is related to
a method that includes receiving, by a device, information
identifying a job site, a load zone of the job site, a dump zone of
the job site, a quantity of loads, and a material associated with
the load zone and the dump zone. The method may include
identifying, by the device, a machine from multiple machines
available for the job site, based on information about the multiple
machines, information about drivers of the multiple machines,
information about a geographical area in which the load zone and
the dump zone are located, or information about a condition
associated with the geographical area. The method may include
providing, by the device and to a user device associated with the
machine, information indicating that the load zone, the dump zone,
the quantity of loads, and the material are assigned to the
machine, and receiving, by the device, from the user device, and
over a time period, location information associated with the user
device and the machine. The method may include determining, by the
device, statuses of the machine over the time period and based on
the location information, and calculating, by the device, a dump
count of the material, for the machine and at a particular time,
based on the statuses of the machine. The method may include
performing, by the device, an action based on the dump count of the
material.
BRIEF DESCRIPTION OF THE DRAWINGS
[0010] FIGS. 1-10 are diagrams of example implementations described
herein;
[0011] FIG. 11 is a diagram of an example environment in which
systems and/or methods, described herein, may be implemented;
[0012] FIG. 12 is a diagram of example components of one or more
devices of FIG. 11; and
[0013] FIG. 13 is a flow chart of an example process for managing
material delivery productivity.
DETAILED DESCRIPTION
[0014] This disclosure relates to a management platform that
manages material delivery productivity. The management platform has
universal applicability to any machine that handles earthen
materials, such as a dump trucks, a bulldozer, an excavator, a
continuous miner, a loader, and/or the like.
[0015] FIGS. 1-10 are diagrams of example implementations described
herein. As shown in example implementation 100 of FIG. 1, a first
user device may be associated with a machine operator, a second
user device may be associated with a site foreman, and the user
devices may be associated with a management platform. As further
shown in FIG. 1, and by reference number 110, the management
platform may provide a material management application to the first
user device and the second user device. In some implementations,
the first user device and/or the second user device may request the
material management application from the management platform, and
may download the material management application from the
management platform (e.g., with approval of the management
platform). In some implementations, the material management
application may include an application that enables management of
material delivery productivity, site planning, visualization of
analytics results, monitoring of a job site, and/or the like (e.g.,
by the management platform, the machine operator, the site foreman,
and/or the like).
[0016] In some implementations, the machine operator and the site
foreman may install the material management application on the
first user device and the second user device, respectively, and may
provide user settings for the material management application. In
some implementations, the user settings may include information
indicating a user name (e.g., Pam for the machine operator and Joe
for the site foreman), a title of the user (e.g., driver and
foreman), a password for the application, whether the user wishes
to work at particular job sites, whether the user wishes work on
particular days or at particular times, whether the user prefers to
work with particular materials, whether the user wishes to receive
alerts associated with the job site, whether the user wishes to
receive material delivery productivity data, a calendar of the
user, user information (e.g., years of experience, experience on
similar jobs, ratings, when the user last worked, etc.), machine
information (e.g., where the machine is located, an age of the
machine, a maintenance record of the machine, a future scheduled
maintenance or repair for the machine, how many miles are on the
machine, how many miles are on tires and/or tread on the machine),
and/or the like. As further shown in FIG. 1, and by reference
number 120, the management platform may receive the user settings
from the first user device and the second user device, and may
store the user settings in a memory associated with the management
platform.
[0017] As shown in example implementation 200 of FIG. 2, the site
foreman may utilize the material management application, via the
user device, to manage a job site. For example, as shown by
reference number 210, the user device may provide for display, to
the site foreman, a user interface that enables the site foreman to
create a job site. In some implementations, the site foreman may
utilize the user interface to retrieve (e.g., from a memory of the
user device or from another source) a visual rendering of the job
site. The visual rendering of the job site may include a satellite
image, a topographical map, a topological map, a dot map, a road
map, a hybrid map, and/or the like of the job site.
[0018] As further shown in FIG. 2, and by reference number 220, the
user device may provide for display, to the site foreman, a user
interface that provides the visual rendering of the job site and
enables the site foreman to create load zones (e.g., zones where a
machine loads a material for hauling) for the job site. As further
shown in FIG. 2, and by reference number 230, the user device may
provide for display, to the site foreman, a user interface that
enables the site foreman to define the load zones via the visual
rendering of the job site. In some implementations, to create load
zones (e.g., load zones A and B), the site foreman may utilize a
finger or a stylus with the user interface to create multi-polygon
geographical boundaries or geo-fences that represent the load
zones. In such implementations, the site foreman may utilize the
finger or the stylus to tap a particular quantity of corners for a
polygon that represents a load zone. In some implementations, the
site foreman need not create load zones, and the load zones may be
automatically defined by a location of a machine that performs the
loading (e.g., an excavator, a loader, and/or the like). In such
implementations, the management platform may track the location of
the loading machine (e.g., via a user device associated with the
loading machine), and may assign a load zone to the location of the
loading machine. The location of load zone, in such
implementations, may change as the loading machine moves around the
job site.
[0019] As shown in example implementation 300 of FIG. 3, and by
reference number 310, the user device may provide for display, to
the site foreman, a user interface that provides the visual
rendering of the job site and enables the site foreman to create
dump zones for the job site and a quantity of loads associated with
the job site. As further shown in FIG. 3, and by reference number
320, the user device may provide for display, to the site foreman,
a user interface that enables the site foreman to define the dump
zones via the visual rendering of the job site. In some
implementations, to create dump zones (e.g., dump zones Y and Z),
the site foreman may utilize a finger or a stylus with the user
interface to create multi-polygon geographical boundaries or
geo-fences that represent the dump zones. In such implementations,
the site foreman may utilize the finger or the stylus to tap a
particular quantity of corners for a polygon that represents a dump
zone.
[0020] As further shown in FIG. 3, and by reference number 330, the
user device may provide for display, to the site foreman, a user
interface that enables the site foreman to define materials for the
load zones and the dump zones, and a quantity of loads for dumping
at the dump zones. For example, the site foreman may indicate, via
the user interface, that load zone A includes stone as a material
and that load zone B includes sand as a material. The site foreman
may also indicate, via the user interface, that one-hundred (100)
loads of sand, from load zone A, are to be dumped at dump zone Y,
and that fifty (50) loads of stone, from load zone B, are to be
dumped at dump zone Z. In some implementations, the site foreman
may continue to utilize the material management application to
define other job sites, load zones, dump zones, materials, quantity
of loads, and/or the like.
[0021] As shown in example implementation 400 of FIG. 4, and by
reference number 410, the management platform may receive
information identifying the job site, the load zones, the dump
zones, the quantity of loads, and the materials associated with the
zones. In some implementations, when the site foreman has provided
all of the information for the job site, the user device may
provide an option to provide the information to the management
platform. When the site foreman selects the option, the selection
of the option may cause the user device to provide, to the
management platform, the information identifying the job site, the
load zones, the dump zones, the quantity of loads, and the
materials associated with the zones. In some implementations, the
management platform may store the information identifying the job
site, the load zones, the dump zones, the quantity of loads, and
the materials associated with the zones in a memory associated with
the management platform.
[0022] As shown in example implementation 500 of FIG. 5, and by
reference number 510, the management platform may identify one or
more machines (e.g., dump trucks), from multiple machines available
for the job site, to assign to the job site (e.g., for loading,
hauling, and dumping materials). In some implementations, the
management platform may utilize a variety of information (e.g.,
associated with the multiple machines) to identify or select the
one or more machines from the multiple machines. For example, the
management platform may utilize machine operator information (e.g.,
years of experience, experience on similar jobs, ratings, when the
machine operators last worked, etc.), where machines are located,
ages of the machines, maintenance records of the machines, future
scheduled maintenance or repair for the machines, how many miles
are on the machines, how many miles are on tires and/or tracts of
the machines, weather forecast information, geographical topography
information for the job site (e.g., hills, valleys, flat, etc.),
information about a condition associated with the job site (e.g.,
muddy, dusty, paved roads, etc.), and/or the like.
[0023] In some implementations, the management platform may assign
weights to the variety of information used to identify the one or
more machines, and may determine scores for the multiple machines
based on the weights. The management platform may assign ranks to
the multiple machines based on the scores, and may identify the one
or more machines based on the ranks of the multiple machines. For
example, if the job site requires five dump trucks, the management
platform may identify five dump trucks with the highest ranks for
the job site.
[0024] As further shown in FIG. 5, and by reference number 520,
once the management platform identifies the one or more machines
(e.g., dump trucks), the management platform may provide
invitations, to work on the job site, to user devices associated
with the one or more machines. For example, the management platform
may provide an invitation, to work on the job site, to a user
device associated with dump truck driver M, another invitation, to
work on the job site, to a user device associated with dump truck
driver P, and/or the like.
[0025] The user devices may receive the invitations, and may
provide for display user interfaces indicating the invitation to
work on the job site. The user interfaces may also enable dump
truck driver M and dump truck driver P to accept the invitations to
work on the job site, which may cause the user devices to provide
acceptances to the management platform. As further shown in FIG. 5,
and by reference number 530, if the dump truck drivers accept the
invitations, the management platform may receive acceptances to the
invitations from the user devices associated with dump truck driver
M and dump truck driver P.
[0026] As shown in example implementation 600 of FIG. 6, and by
reference number 610, the management platform may add the machines
(e.g., the dump trucks) to the job site. In some implementations,
by adding the dump trucks to the job site, the management platform
may indicate that the dump trucks are available to perform work
(e.g., loading, hauling, dumping, and/or the like) on the job
site.
[0027] As further shown in FIG. 6, and by reference number 620, the
management platform may provide assignments, associated with the
job site, to user devices associated with the one or more machines.
For example, the management platform may provide an assignment to
the user device associated with dump truck driver M, another
assignment to the user device associated with dump truck driver P,
and/or the like. In some implementations, each assignment may
include information indicating that a load zone, a dump zone, a
quantity of loads, and a material are assigned to the machine
(e.g., the dump truck). In some implementations, the user device
may provide for display (e.g., via a user interface) the
information included in the assignments. For example, the user
device for dump truck driver M may indicate that dump truck driver
M is to retrieve fifty (50) loads of stone from load zone A, haul
the stone to dump zone Z, and dump the stone at dump zone Z. In
another example, the user device for dump truck driver P may
indicate that dump truck driver P is to retrieve one-hundred (100)
loads of sand from load zone B, haul the sand to dump zone Y, and
dump the sand at dump zone Y.
[0028] In some implementations, the assignments may include
navigation information that provides directions to and from load
zones and dump zones associated with different machines. For
example, the assignment may cause the user device associated with
dump truck driver M to provide navigation information to and from
load zone A and dump zone Z. In another example, the assignment may
cause the user device associated with dump truck driver P to
provide navigation information to and from load zone B and dump
zone Y.
[0029] In some implementations, if a machine is an autonomous
vehicle, the management platform may provide an assignment to the
machine, and the assignment may include instructions for performing
tasks on the job site. For example, if the machine is an autonomous
dump truck, the management platform may provide, to the dump truck,
instructions that cause the dump truck to load material from a load
zone, haul the material to a dump zone, dump the material at the
dump zone, and repeat the aforementioned steps.
[0030] As shown in example implementation 700 of FIG. 7, and by
reference number 710, the management platform may receive, from
user devices associated with the machines and over a time period
(e.g., in minutes, hours, days, weeks, etc.), location information
associated with the user devices and the machines. In some
implementations, the location information for the machines may be
the same as associated user devices since the user devices may be
physically provided in the machines. In some implementations, the
management platform may continuously track locations of all
machines working on the job site based on locations (e.g., global
positioning system (GPS) coordinates) of the user devices provided
in the machines. Since many of the machines (e.g., dump trucks) on
the job site move around the job site, the management platform may
continuously track current locations of such machines. In some
implementations, the machines may include sensors (e.g., that
communicate with the management platform and/or user devices) that
provide information indicating how many times a dump truck received
a load, how many times a dump truck dumps a load, how many times an
excavator bucket engages the ground, is filled, and is emptied,
and/or the like.
[0031] For example, assume that user devices are provided in dump
truck M, dump truck P, and excavators shown in FIG. 7. In such an
example, the management platform may track the locations of dump
truck M, dump truck P, and the excavators based on the locations of
user devices provided in dump truck M, dump truck P, and the
excavators. As shown, one excavator may be located near load zone
A, dump truck P and the other excavator may be located near load
zone B, and dump truck M may be located near dump zone Z, at a
particular time. In some implementations, the management platform
may store the location information associated with the user devices
and the machines in a memory associated with the management
platform.
[0032] As shown in example implementation 800 of FIG. 8, the
management platform may determine statuses of a machine (e.g., a
dump truck) over the time period and based on the location
information associated with the machine. In some implementations,
and as indicated by reference number 810 in FIG. 8, the management
platform may determine that the dump truck status is loading when
the location of the dump truck is within a particular distance
(e.g., B centimeters, meters, etc.) of a matching material load
zone (e.g., a load zone that includes the material assigned to the
dump truck) for more than a particular time period (e.g., A
seconds, minutes, etc.). In some implementations, the dump truck
may include sensors (e.g., communicating with the management
platform and/or the user device) that provide information
indicating whether the dump truck has received a load.
[0033] In some implementations, and as indicated by reference
number 820 in FIG. 8, the management platform may determine that
the dump truck status is hauling a load when the location of the
dump truck is outside of any zone (e.g., load zones or dump zones)
for more than a particular time period (e.g., C seconds, minutes,
etc.).
[0034] In some implementations, and as indicated by reference
number 830 in FIG. 8, the management platform may determine that
the dump truck status is dumping a load when the location of the
dump truck is within a particular distance (e.g., D centimeters,
meters, etc.) of a matching material dump zone (e.g., a dump zone
that includes the material assigned to the dump truck) for more
than a particular time period (e.g., E seconds, minutes, etc.). In
some implementations, the dump truck may include sensors (e.g.,
communicating with the management platform and/or the user device)
that provide information indicating that the dump truck dumped a
load.
[0035] In some implementations, and as indicated by reference
number 840 in FIG. 8, the management platform may determine that
the dump truck status is returning to a load zone after dumping a
load when the location of the dump truck is outside of any zone
(e.g., load zones or dump zones) for more than a particular time
period (e.g., C seconds, minutes, etc.).
[0036] In some implementations, and as indicated by reference
number 850 in FIG. 8, the management platform may determine that
the dump truck status is entering the load zone again when the
location of the dump truck is within a particular distance (e.g., F
centimeters, meters, etc.) of the matching material load zone
(e.g., a load zone that includes the material assigned to the dump
truck) for more than a particular time period (e.g., G seconds,
minutes, etc.).
[0037] In some implementations, the particular distance thresholds
(e.g., B, D, and F) and the particular time period thresholds
(e.g., A, C, E, and G) may be provided by an operator of the
management platform. In some implementations, the particular
distance thresholds (e.g., B, D, and F) and the particular time
period thresholds (e.g., A, C, E, and G) may be determined by the
management platform based on historical loading and dumping
information associated with the job site. For example, the
management platform may utilize the historical loading and dumping
information to train a machine learning model to determine values
for the particular distance thresholds and/or particular time
period thresholds. In some implementations, the management platform
may train the machine learning model (e.g., to generate a trained
machine learning model) by providing the historical loading and
dumping information (e.g., training data) to the machine learning
model, and receiving predictions (e.g., indicating predicted
events) based on providing the historical loading and dumping
information to the machine learning model. Based on the
predictions, the management platform may update the machine
learning model, and may provide the historical loading and dumping
information to the updated machine learning model. The management
platform may repeat this process until correct predictions are
generated by the machine learning model.
[0038] In some implementations, the machine learning model may
include a supervised machine learning model, an unsupervised
machine learning model, and/or the like. The supervised machine
learning model may learn a function that maps an input to an output
based on example input-output pairs. The machine learning model
infers a function from labeled training data consisting of a set of
training examples. Each example may be a pair consisting of an
input object (typically a vector) and a desired output value (also
called the supervisory signal). A supervised machine learning model
may analyze the training data and produce an inferred function,
which can be used for mapping new examples. In some
implementations, an optimal scenario will allow for the supervised
machine learning model to correctly determine class labels for
unseen instances. In this case, correctly determining the class
labels for unseen instances may require the supervised machine
learning model to generalize from the training data to unseen
situations in a reasonable way, such as through application of
inductive bias.
[0039] In order to solve a given problem using a supervised machine
learning model, a type of training example may first be determined,
a training set may be gathered, an input feature representation of
a learned function may be determined, the structure of the learned
function and corresponding supervised machine learning model may be
determined, the supervised machine learning model may be executed
on the gathered training set, and the accuracy of the learned
function may be evaluated. The supervised machine learning model
may include a support vector machine, a linear regression model, a
logistic regression model, a naive Bayes classifier, a linear
discriminant analysis model, a decision tree, a k-nearest neighbor
model, an artificial neural network, and/or the like.
[0040] The unsupervised machine learning model may infer a function
to describe hidden structure from unlabeled data. Because the
examples given to the learner are unlabeled, unlike supervised
learning, there is no evaluation of an accuracy of structure that
is output by the unsupervised machine learning model.
[0041] The unsupervised machine learning model may include a
clustering model (e.g., a k-means clustering model, a mixture
model, a hierarchical clustering model, and/or the like), an
anomaly detection model, an artificial neural network (e.g., an
autoencoder, a deep belief net, a Hebbian learning model, a
generative adversarial network, a self-organizing map, and/or the
like), a latent variable model (e.g., an expectation-maximization
model, a method of moments model, a blind signal separation model),
and/or the like.
[0042] In some implementations, the management platform may utilize
one or more of the trained machine learning models, and may utilize
the best results determined by one of the trained machine learning
models. In some implementations, the management platform may
utilize a plurality of the trained machine learning models, and may
aggregate the results determined by the plurality of trained
machine learning models.
[0043] As further shown in FIG. 8, the management platform may
determine a dump count for the dump truck by adding a quantity of
times that the dump truck includes consecutive loading, hauling,
and dumping statuses (e.g., as indicated by reference numbers 810,
820, and 830) over the time period. As further shown in FIG. 8, the
management platform may determine a quantity of material delivery
cycles for the dump truck by adding a quantity of times that the
dump truck includes consecutive loading, hauling, dumping,
returning, and entering statuses (e.g., as indicated by reference
numbers 810, 820, 830, 840, and 850) over the time period.
[0044] As shown in example implementation 900 of FIG. 9, and by
reference number 910, the management platform may provide material
delivery productivity information to the user device associated
with the site foreman. In some implementations, the material
delivery productivity information may include information
indicating dump counts for dump trucks, quantities of material
delivery cycles for dump trucks, routes traveled by dump trucks,
distances traveled by dump trucks, average speeds of dump trucks,
and/or the like. In some implementations, the dump truck may
include sensors (e.g., communicating with the management platform
and/or the user device) that provide information indicating routes
traveled by the dump truck, quantities of material delivered by the
dump truck, a weight of the dump truck, a time to deliver material
by the dump truck, a quantity of material hauled per trip, and/or
the like. In some implementations, the user device may receive the
material delivery productivity information and may provide the
information for display via a variety of user interfaces to the
site foreman.
[0045] As further shown in FIG. 9, and by reference number 920, the
user device may provide for display, to the site foreman, a user
interface that provides a route traveled by a particular dump truck
on the job site. For example, the route may indicate that the
particular dump truck loaded stone at load zone A, traveled from
load zone A to dump zone Z, dumped the stone at dump zone Z, and
returned to load zone A, a number of times.
[0046] As further shown in FIG. 9, and by reference number 930, the
user device may provide for display, to the site foreman, a user
interface that provides, in real time, current dump counts at the
dump zones of the job site. For example, the user interface may
indicate that ten (10) loads of sand have been dumped at dump zone
Y, and that ninety (90) more loads of sand are needed at dump zone
Y. The user interface may also indicate that twenty-six (26) loads
of stone have been dumped at dump zone Z, and that twenty-four (24)
more loads of stone are needed at dump zone Z.
[0047] As further shown in FIG. 9, and by reference number 940, the
user device may provide for display, to the site foreman, a user
interface that provides material delivery productivity information
for a particular dump truck on the job site. For example, the user
interface may indicate that particular dump truck has spent 6.9% of
the time period loading material, 43.2% of the time period dumping
the material, 13.6% of the time period hauling the material, and
36.3% of the time period returning to a load zone for the material.
The user interface may also indicate that the particular dump truck
traveled a total distance of 3.8 miles over the time period,
traveled at an average speed of 7.9 miles per hour (mph) over the
time period, and has completed thirteen (13) material delivery
cycles over the time period.
[0048] In some implementations, and with reference to example
implementation 1000 of FIG. 10, the management platform may perform
an action based on the dump count of the material and the quantity
of material delivery cycles. For example, as shown by reference
number 1010 in FIG. 10, the action performed by management platform
may include revising assignments for the dump trucks. In such an
example, and as shown by reference number 1020, the management
platform may provide a revision to the load zone, the dump zone,
the material to transport, and the quantity of loads to the user
device associated with dump truck driver M. In the example, the
revision may include requiring a lesser quantity of loads from dump
truck driver M (e.g., reduced from 50 to 25 loads since dump truck
driver M is behind in loads of stone).
[0049] As further shown in FIG. 10, and by reference number 1030,
the management platform may provide a revision to the load zone,
the dump zone, the material to transport, and the quantity of loads
to the user device associated with dump truck driver P. In the
example, the revision may include requiring a different load zone
(e.g., load zone A), a different material (e.g., stone), a
different dump zone (e.g., dump zone Z), and a quantity of loads
from dump truck driver P (e.g., to help dump truck driver M who is
behind in loads of stone).
[0050] In some implementations, the action performed by the
management platform may include providing, to the user device
associated with the site foreman, information identifying a dump
count of a material and a quantity of material delivery cycles. In
this way, the site foreman may track productivity of the dump
trucks and may rate the dump truck drivers for future
reference.
[0051] In some implementations, the action performed by the
management platform may include providing, to the user device
associated with the dump truck driver, one or more alerts
associated with the dump count of the material or the quantity of
material delivery cycles. In this way, the dump truck driver may
track such information and may determine how much the dump truck
driver will get paid. In some implementations, the management
platform may control an excavator or a backhoe that provides the
material to the dump truck. In such implementations, the management
platform may know that a particular dump truck operates most
efficiently with particular weight of material, and may instruct
the excavator or backhoe to fill the dump with the particular
weight.
[0052] As indicated above, FIGS. 1-10 are provided merely as
examples. Other examples are possible and may differ from what was
described with regard to FIGS. 1-10.
[0053] FIG. 11 is a diagram of an example environment 1100 in which
systems and/or methods, described herein, may be implemented. As
shown in FIG. 11, environment 1100 may include a user device 1110,
a management platform 1120, and a network 1130. Devices of
environment 1100 may interconnect via wired connections, wireless
connections, or a combination of wired and wireless
connections.
[0054] User device 1110 includes one or more devices capable of
receiving, generating, storing, processing, and/or providing
information, such as information described herein. For example,
user device 1110 may include a mobile phone (e.g., a smart phone, a
radiotelephone, etc.), a laptop computer, a tablet computer, a
desktop computer, a handheld computer, a gaming device, a wearable
communication device (e.g., a smart wristwatch, a pair of smart
eyeglasses, etc.), or a similar type of device. In some
implementations, user device 1110 may receive information from
and/or transmit information to management platform 1120.
[0055] Management platform 1120 includes one or more devices that
manage material delivery productivity associated with a machine
(e.g., associated with user device 1110). In some implementations,
management platform 1120 may be designed to be modular such that
certain software components may be swapped in or out depending on a
particular need. As such, management platform 1120 may be easily
and/or quickly reconfigured for different uses. In some
implementations, management platform 1120 may receive information
from and/or transmit information to one or more user devices
1110.
[0056] In some implementations, as shown, management platform 1120
may be hosted in a cloud computing environment 1122. Notably, while
implementations described herein describe management platform 1120
as being hosted in a cloud computing environment 1122, in some
implementations, management platform 1120 may not be cloud-based
(i.e., may be implemented outside of a cloud computing environment)
or may be partially cloud-based.
[0057] Cloud computing environment 1122 includes an environment
that hosts management platform 1120. Cloud computing environment
1122 may provide computation, software, data access, storage, etc.
services that do not require end-user knowledge of a physical
location and configuration of system(s) and/or device(s) that hosts
management platform 1120. As shown, cloud computing environment
1122 may include a group of computing resources 1124 (referred to
collectively as "computing resources 1124" and individually as
"computing resource 1124").
[0058] Computing resource 1124 includes one or more personal
computers, workstation computers, server devices, or other types of
computation and/or communication devices. In some implementations,
computing resource 1124 may host management platform 1120. Cloud
resources may include compute instances executing in computing
resource 1124, storage devices provided in computing resource 1124,
data transfer devices provided by computing resource 1124, etc. In
some implementations, computing resource 1124 may communicate with
other computing resources 1124 via wired connections, wireless
connections, or a combination of wired and wireless
connections.
[0059] As further shown in FIG. 11, computing resource 1124
includes a group of cloud resources, such as one or more
applications ("APPs") 1124-1, one or more virtual machines ("VMs")
1124-2, virtualized storage ("VSs") 1124-3, one or more hypervisors
("HYPs") 1124-4, and/or the like.
[0060] Application 1124-1 includes one or more software
applications that may be provided to or accessed by user device
1110. Application 1124-1 may eliminate a need to install and
execute the software applications on user device 1110. For example,
application 1124-1 may include software associated with management
platform 1120 and/or any other software capable of being provided
via cloud computing environment 1122. In some implementations, one
application 1124-1 may send/receive information to/from one or more
other applications 1124-1, via virtual machine 1124-2.
[0061] Virtual machine 1124-2 includes a software implementation of
a machine (e.g., a computer) that executes programs like a physical
machine. Virtual machine 1124-2 may be either a system virtual
machine or a process virtual machine, depending upon use and degree
of correspondence to any real machine by virtual machine 1124-2. A
system virtual machine may provide a complete system platform that
supports execution of a complete operating system ("OS"). A process
virtual machine may execute a single program, and may support a
single process. In some implementations, virtual machine 1124-2 may
execute on behalf of a user (e.g., a user of user device 1110 or an
operator of management platform 1120), and may manage
infrastructure of cloud computing environment 1122, such as data
management, synchronization, or long-duration data transfers.
[0062] Virtualized storage 1124-3 includes one or more storage
systems and/or one or more devices that use virtualization
techniques within the storage systems or devices of computing
resource 1124. In some implementations, within the context of a
storage system, types of virtualizations may include block
virtualization and file virtualization. Block virtualization may
refer to abstraction (or separation) of logical storage from
physical storage so that the storage system may be accessed without
regard to physical storage or heterogeneous structure. The
separation may permit administrators of the storage system
flexibility in how the administrators manage storage for end users.
File virtualization may eliminate dependencies between data
accessed at a file level and a location where files are physically
stored. This may enable optimization of storage use, server
consolidation, and/or performance of non-disruptive file
migrations.
[0063] Hypervisor 1124-4 may provide hardware virtualization
techniques that allow multiple operating systems (e.g., "guest
operating systems") to execute concurrently on a host computer,
such as computing resource 1124. Hypervisor 1124-4 may present a
virtual operating platform to the guest operating systems, and may
manage the execution of the guest operating systems. Multiple
instances of a variety of operating systems may share virtualized
hardware resources.
[0064] Network 1130 includes one or more wired and/or wireless
networks. For example, network 1130 may include a cellular network
(e.g., a fifth generation (5G) network, a long-term evolution (LTE)
network, a third generation (3G) network, a code division multiple
access (CDMA) network, etc.), a public land mobile network (PLMN),
a local area network (LAN), a wide area network (WAN), a
metropolitan area network (MAN), a telephone network (e.g., the
Public Switched Telephone Network (PSTN)), a private network, an ad
hoc network, an intranet, the Internet, a fiber optic-based
network, and/or the like, and/or a combination of these or other
types of networks.
[0065] The number and arrangement of devices and networks shown in
FIG. 11 are provided as an example. In practice, there may be
additional devices and/or networks, fewer devices and/or networks,
different devices and/or networks, or differently arranged devices
and/or networks than those shown in FIG. 11. Furthermore, two or
more devices shown in FIG. 11 may be implemented within a single
device, or a single device shown in FIG. 11 may be implemented as
multiple, distributed devices. Additionally, or alternatively, a
set of devices (e.g., one or more devices) of environment 1100 may
perform one or more functions described as being performed by
another set of devices of environment 1100.
[0066] FIG. 12 is a diagram of example components of a device 1200.
Device 1200 may correspond to user device 1110, management platform
1120, and/or computing resource 1124. In some implementations, user
device 1110, management platform 1120, and/or computing resource
1124 may include one or more devices 1200 and/or one or more
components of device 1200. As shown in FIG. 12, device 1200 may
include a bus 1210, a processor 1220, a memory 1230, a storage
component 1240, an input component 1250, an output component 1260,
and a communication interface 1270.
[0067] Bus 1210 includes a component that permits communication
among the components of device 1200. Processor 1220 is implemented
in hardware, firmware, or a combination of hardware and software.
Processor 1220 is a central processing unit (CPU), a graphics
processing unit (GPU), an accelerated processing unit (APU), a
microprocessor, a microcontroller, a digital signal processor
(DSP), a field-programmable gate array (FPGA), an
application-specific integrated circuit (ASIC), or another type of
processing component. In some implementations, processor 1220
includes one or more processors capable of being programmed to
perform a function. Memory 1230 includes a random access memory
(RAM), a read only memory (ROM), and/or another type of dynamic or
static storage device (e.g., a flash memory, a magnetic memory,
and/or an optical memory) that stores information and/or
instructions for use by processor 1220.
[0068] Storage component 1240 stores information and/or software
related to the operation and use of device 1200. For example,
storage component 1240 may include a hard disk (e.g., a magnetic
disk, an optical disk, a magneto-optic disk, and/or a solid state
disk), a compact disc (CD), a digital versatile disc (DVD), a
floppy disk, a cartridge, a magnetic tape, and/or another type of
non-transitory computer-readable medium, along with a corresponding
drive.
[0069] Input component 1250 includes a component that permits
device 1200 to receive information, such as via user input (e.g., a
touch screen display, a keyboard, a keypad, a mouse, a button, a
switch, and/or a microphone). Additionally, or alternatively, input
component 1250 may include a sensor for sensing information (e.g.,
a global positioning system (GPS) component, an accelerometer, a
gyroscope, and/or an actuator). Output component 1260 includes a
component that provides output information from device 1200 (e.g.,
a display, a speaker, and/or one or more light-emitting diodes
(LEDs)).
[0070] Communication interface 1270 includes a transceiver-like
component (e.g., a transceiver and/or a separate receiver and
transmitter) that enables device 1200 to communicate with other
devices, such as via a wired connection, a wireless connection, or
a combination of wired and wireless connections. Communication
interface 1270 may permit device 1200 to receive information from
another device and/or provide information to another device. For
example, communication interface 1270 may include an Ethernet
interface, an optical interface, a coaxial interface, an infrared
interface, a radio frequency (RF) interface, a universal serial bus
(USB) interface, a Wi-Fi interface, a cellular network interface,
and/or the like.
[0071] Device 1200 may perform one or more processes described
herein. Device 1200 may perform these processes based on processor
1220 executing software instructions stored by a non-transitory
computer-readable medium, such as memory 1230 and/or storage
component 1240. A computer-readable medium is defined herein as a
non-transitory memory device. A memory device includes memory space
within a single physical storage device or memory space spread
across multiple physical storage devices.
[0072] Software instructions may be read into memory 1230 and/or
storage component 1240 from another computer-readable medium or
from another device via communication interface 1270. When
executed, software instructions stored in memory 1230 and/or
storage component 1240 may cause processor 1220 to perform one or
more processes described herein. Additionally, or alternatively,
hardwired circuitry may be used in place of or in combination with
software instructions to perform one or more processes described
herein. Thus, implementations described herein are not limited to
any specific combination of hardware circuitry and software.
[0073] The number and arrangement of components shown in FIG. 12
are provided as an example. In practice, device 1200 may include
additional components, fewer components, different components, or
differently arranged components than those shown in FIG. 12.
Additionally, or alternatively, a set of components (e.g., one or
more components) of device 1200 may perform one or more functions
described as being performed by another set of components of device
1200.
[0074] FIG. 13 is a flow chart of an example process 1300 for
managing material delivery productivity. In some implementations,
one or more process blocks of FIG. 13 may be performed by a
management platform (e.g., management platform 1120). In some
implementations, one or more process blocks of FIG. 13 may be
performed by another device or a group of devices separate from or
including management platform 1120, such as user device 1110.
[0075] As shown in FIG. 13, process 1300 may include receiving
information identifying a job site, a load zone, a dump zone, a
quantity of loads, and a material for the zones (block 1310). For
example, the management platform (e.g., using computing resource
1124, processor 1220, communication interface 1270, and/or the
like) may receive information identifying a job site, a load zone,
a dump zone, a quantity of loads, and a material for the zones, as
described above in connection with FIGS. 1-11.
[0076] As further shown in FIG. 13, process 1300 may include
identifying a machine, from multiple machines, to assign to the
load zone, the dump zone, the quantity of loads, and the material
(block 1320). For example, the management platform (e.g., using
computing resource 1124, processor 1220, storage component 1240,
and/or the like) may identify a machine, from multiple machines, to
assign to the load zone, the dump zone, the quantity of loads, and
the material, as described above in connection with FIGS. 1-11.
[0077] As further shown in FIG. 13, process 1300 may include
providing, to a user device associated with the machine,
information indicating that the load zone, the dump zone, the
quantity of loads, and the material are assigned to the machine
(block 1330). For example, the management platform (e.g., using
computing resource 1124, processor 1220, communication interface
1270, and/or the like) may provide, to a user device associated
with the machine, information indicating that the load zone, the
dump zone, the quantity of loads, and the material are assigned to
the machine, as described above in connection with FIGS. 1-11.
[0078] As further shown in FIG. 13, process 1300 may include
receiving, from the user device and over a time period, location
information associated with the user device and the machine (block
1340). For example, the management platform (e.g., using computing
resource 1124, processor 1220, communication interface 1270, and/or
the like) may receive, from the user device and over a time period,
location information associated with the user device and the
machine, as described above in connection with FIGS. 1-11.
[0079] As further shown in FIG. 13, process 1300 may include
determining statuses of the machine over the time period and based
on the location information (block 1350). For example, the
management platform (e.g., using computing resource 1124, processor
1220, storage component 1240, and/or the like) may determine
statuses of the machine over the time period and based on the
location information, as described above in connection with FIGS.
1-11.
[0080] As further shown in FIG. 13, process 1300 may include
calculating a dump count of the material, for the machine and at a
particular time, based on the statuses of the machine (block 1360).
For example, the management platform (e.g., using computing
resource 1124, processor 1220, memory 1230, and/or the like) may
calculate a dump count of the material, for the machine and at a
particular time, based on the statuses of the machine, as described
above in connection with FIGS. 1-11.
[0081] As further shown in FIG. 13, process 1300 may include
calculate a quantity of material delivery cycles, for the machine
and at the particular time, based on the statuses of the machine
(block 1370). For example, the management platform (e.g., using
computing resource 1124, processor 1220, storage component 1240,
and/or the like) may calculate a quantity of material delivery
cycles, for the machine and at the particular time, based on the
statuses of the machine, as described above in connection with
FIGS. 1-11.
[0082] As further shown in FIG. 13, process 1300 may include
performing an action based on the dump count of the material and
the quantity of material delivery cycles (block 1380). For example,
the management platform (e.g., using computing resource 1124,
processor 1220, memory 1230, communication interface 1270, and/or
the like) may perform an action based on the dump count of the
material and the quantity of material delivery cycles, as described
above in connection with FIGS. 1-11.
[0083] Process 1300 may include additional implementations, such as
any single implementation or any combination of implementations
described below and/or described with regard to any other process
described herein.
[0084] In some implementations, the information identifying the
load zone of the job site and the dump zone of the job site may be
provided via geographical boundaries that are input to a user
interface displaying a visual rendering of the job site. In some
implementations, the management platform may provide, to a user
device associated with a foreman of the job site, information
identifying the dump count of the material and the quantity of
material delivery cycles, may provide, to a user device associated
with the machine, an update to the information indicating that the
load zone, the dump zone, the quantity of loads, and the material
are assigned to the machine, and/or may provide, to a user device
associated with another machine, information indicating that the
load zone, the dump zone, a portion of the quantity of loads, and
the material are assigned to the other machine.
[0085] In some implementations, the management platform may
determine, based on the statuses of the machine, a first quantity
of times the machine is located at or near the load zone, may
determine, based on the statuses of the machine, a second quantity
of times the machine is located between the load zone and the dump
zone, may determine, based on the statuses of the machine, a third
quantity of times the machine is located at or near the dump zone,
and may calculate the dump count of the material based on the first
quantity of times, the second quantity of times, and the third
quantity of times.
[0086] In some implementations, the management platform may
determine, based on the statuses of the machine, a first quantity
of times the machine is located at or near the load zone, may
determine, based on the statuses of the machine, a second quantity
of times the machine is traveling from the load zone to the dump
zone, may determine, based on the statuses of the machine, a third
quantity of times the machine is located at or near the dump zone,
may determine, based on the statuses of the machine, a fourth
quantity of times the machine is traveling from the dump zone to
the load zone, and may calculate the quantity of material delivery
cycles based on the first quantity of times, the second quantity of
times, the third quantity of times, and the fourth quantity of
times.
[0087] In some implementations, the management platform may
identify the machine based on the information identifying the job
site, the load zone, the dump zone, the quantity of loads, and the
material, and may provide, to the user device, the information
indicating that the load zone, the dump zone, the quantity of
loads, and the material are assigned to the machine, based on
identifying the machine. In some implementations, the machine may
include a dump truck.
[0088] In some implementations, the action may include one or more
of providing, to the first user device or the second user device,
information identifying the dump count of the material and the
quantity of material delivery cycles, providing, to the first user
device, one or more alerts associated with the dump count of the
material or the quantity of material delivery cycles, providing, to
the second user device, an update to the information indicating
that the load zone, the dump zone, the quantity of loads, and the
material are assigned to the machine, and/or providing, to a third
user device associated with another machine, information indicating
that the load zone, the dump zone, a portion of the quantity of
loads, and the material are assigned to the other machine.
[0089] In some implementations, the information identifying the
load zone of the job site may be determined based on a location of
a loader machine on the job site, and the information identifying
the dump zone of the job site may be provided via geographical
boundaries that are input to a user interface displaying a visual
representation of the job site. In some implementations, the
management platform may determine, based on the statuses of the
machine, a quantity of times that the machine is located at or near
the load zone, then is located between the load zone and the dump
zone, and then is located at or near the dump zone, and may
calculate the dump count of the material based on the quantity of
times.
[0090] In some implementations, the management platform may
determine, based on the statuses of the machine, a quantity of
times that the machine is located at or near the load zone, then is
traveling from the load zone to the dump zone, then is located at
or near the dump zone, and then is traveling from the dump zone to
the load zone, and may calculate the quantity of material delivery
cycles based on the quantity of times.
[0091] In some implementations, the statuses of the machine may
indicate that the machine is at or near the load zone when the
machine is located within a first distance of the load zone for a
first amount of time, that the machine is traveling from the load
zone to the dump zone when the machine is located greater than the
first distance from the load zone for a second amount of time after
the first amount of time, that the machine is at or near the dump
zone when the machine is located within a second distance of the
dump zone for a third amount of time, and/or that the machine is
traveling from the dump zone to the load zone when the machine is
located greater than the second distance from the dump zone for a
fourth amount of time after the third amount of time.
[0092] In some implementations, the management platform may monitor
the job site based on the statuses of the machine and based on
statuses of another machine on the job site, may generate one or
more alerts based on monitoring the job site, and may provide the
one or more alerts to the first user device. In some
implementations, the management platform may monitor the job site
based on the statuses of the machine, may generate material
delivery productivity information based on monitoring the job site,
and may provide the material delivery productivity information to
another user device associated with a foreman of the job site.
[0093] Although FIG. 13 shows example blocks of process 1300, in
some implementations, process 1300 may include additional blocks,
fewer blocks, different blocks, or differently arranged blocks than
those depicted in FIG. 13. Additionally, or alternatively, two or
more of the blocks of process 1300 may be performed in
parallel.
INDUSTRIAL APPLICABILITY
[0094] Management platform 1120 may be used to manage material
delivery productivity. In some implementations, management platform
1120 may receive information identifying a job site, a load zone of
the job site, a dump zone of the job site, a quantity of loads, and
a material for the load zone and the dump zone. Management platform
1120 may identify a machine, from multiple machines available for
the job site, to assign to the load zone, the dump zone, the
quantity of loads, and the material, and may provide, to a user
device associated with the machine, information indicating that the
load zone, the dump zone, the quantity of loads, and the material
are assigned to the machine. Management platform 1120 may receive,
from the user device and over a time period, location information
associated with the user device and the machine, and may determine
statuses of the machine over the time period and based on the
location information. Management platform 1120 may calculate a dump
count of the material, for the machine and at a particular time,
based on the statuses of the machine, and may calculate a quantity
of material delivery cycles, for the machine and at the particular
time, based on the statuses of the machine. Management platform
1120 may perform an action based on the dump count of the material
and the quantity of material delivery cycles.
[0095] In this way, several different stages of the process for
managing material delivery productivity are automated, which may
remove human subjectivity and waste from the process, and which may
improve speed and efficiency of the process and conserve computing
resources (e.g., processing resources, memory resources, and/or the
like). Furthermore, implementations described herein use a
rigorous, computerized process to perform tasks or roles that were
not previously performed or were previously performed using
subjective human intuition or input. For example, current systems
require utilizing expensive and difficult to use telemetry hardware
(e.g., embedded or retrofit in a machine) to track materials.
Finally, automating the process for managing material delivery
productivity conserves computing resources (e.g., processing
resources, memory resources, and/or the like) that would otherwise
be wasted in attempting to manage material delivery
productivity.
[0096] As used herein, the articles "a" and "an" are intended to
include one or more items, and may be used interchangeably with
"one or more." Also, as used herein, the terms "has," "have,"
"having," or the like are intended to be open-ended terms. Further,
the phrase "based on" is intended to mean "based, at least in part,
on."
[0097] The foregoing disclosure provides illustration and
description, but is not intended to be exhaustive or to limit the
implementations to the precise form disclosed. Modifications and
variations are possible in light of the above disclosure or may be
acquired from practice of the implementations. It is intended that
the specification be considered as an example only, with a true
scope of the disclosure being indicated by the following claims and
their equivalents. Even though particular combinations of features
are recited in the claims and/or disclosed in the specification,
these combinations are not intended to limit the disclosure of
possible implementations. Although each dependent claim listed
below may directly depend on only one claim, the disclosure of
possible implementations includes each dependent claim in
combination with every other claim in the claim set.
* * * * *